The integration of AI systems into digital processes, retail and logistics is enabling a rapid shift in the speed and performance of many business processes. At the same time, it is accelerating the rate of change. All that data is useless without hands-on support from analysts who evaluate and utilize that information to provide informed business recommendations to decision makers.

What Is An AI Analyst?

Today’s AI analysts are focused on generating, maintaining and delivering detailed and accurate reporting on the information gathered and reported by artificial intelligence systems, with the goal of maximizing ROI from the rush of new data being provided to these companies. These AI systems generate huge volumes of data -- augmenting and, in some cases, replacing human operators in the fields of customer service, transaction processing and software systems.

Just look at the ways big companies like Apple, Facebook, Amazon and Google are using AI in their businesses to enhance operations and improve competition with each other. Take, for instance, Apple’s approach to architecture in its newest devices. The iPhone X and iPhone 8 feature the A11 Bionic chip, which uses machine learning to guide developers in the incorporation of AI functions into apps. Developers likewise must coordinate with analysts who can make sense of the data gathered in their new A11 enhanced apps.

Under CEO Sundar Pichai, Google has fully rebranded itself as an AI-focused company in the last few years. It sees technology as being on the cusp of a social revolution that will change how we interact with machines, and AI is at the center of this transition. Recent product releases like Pixel Buds with its language translation features, Google Home's smart speaker ecosystem, and the updates being made to its SaaS products to integrate more advanced AI systems show the evolution of this philosophy.

Facebook is even more public about its integration of AI into its systems, with facial recognition technology in its photo tagging system dating all the way back in 2010, heavy investment into AI for translation services, video recognition and Facebook Messenger’s natural language processing. That investment comes with caveats as several governments have inquired about how algorithms are policed and monitored, and analysts are stepping up to ensure AI is used as intended to improve the performance of these platforms.